diff --git a/docs/en/models/yolov9.md b/docs/en/models/yolov9.md
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--- a/docs/en/models/yolov9.md
+++ b/docs/en/models/yolov9.md
@@ -169,10 +169,10 @@ This example provides simple YOLOv9 training and inference examples. For full do
 
 The YOLOv9 series offers a range of models, each optimized for high-performance [Object Detection](../tasks/detect.md). These models cater to varying computational needs and accuracy requirements, making them versatile for a wide array of applications.
 
-| Model      | Filenames                                               | Tasks                                        | Inference | Validation | Training | Export |
-| ---------- | ------------------------------------------------------- | -------------------------------------------- | --------- | ---------- | -------- | ------ |
-| YOLOv9     | `yolov9t` `yolov9s` `yolov9m` `yolov9c.pt` `yolov9e.pt` | [Object Detection](../tasks/detect.md)       | ✅        | ✅         | ✅       | ✅     |
-| YOLOv9-seg | `yolov9c-seg.pt` `yolov9e-seg.pt`                       | [Instance Segmentation](../tasks/segment.md) | ✅        | ✅         | ✅       | ✅     |
+| Model      | Filenames                                                        | Tasks                                        | Inference | Validation | Training | Export |
+| ---------- | ---------------------------------------------------------------- | -------------------------------------------- | --------- | ---------- | -------- | ------ |
+| YOLOv9     | `yolov9t.pt` `yolov9s.pt` `yolov9m.pt` `yolov9c.pt` `yolov9e.pt` | [Object Detection](../tasks/detect.md)       | ✅        | ✅         | ✅       | ✅     |
+| YOLOv9-seg | `yolov9c-seg.pt` `yolov9e-seg.pt`                                | [Instance Segmentation](../tasks/segment.md) | ✅        | ✅         | ✅       | ✅     |
 
 This table provides a detailed overview of the YOLOv9 model variants, highlighting their capabilities in object detection tasks and their compatibility with various operational modes such as [Inference](../modes/predict.md), [Validation](../modes/val.md), [Training](../modes/train.md), and [Export](../modes/export.md). This comprehensive support ensures that users can fully leverage the capabilities of YOLOv9 models in a broad range of object detection scenarios.